Yes, you need to have prior experience programming in python.

Yes, upon successfully completing a course, you will receive a certification from TIF Labs. This certification can be a valuable addition to your professional portfolio, showcasing your expertise and skills in the respective field.

The workshop is suitable for individuals interested in AI and machine learning, especially those who want to learn how to implement these technologies on a microcontroller like the Raspberry Pi Pico.

A basic understanding of Deep Learning (neural networks) and programming of any embedded micro-controller would be beneficial. Although not mandatory, the TinyML fitness tracker kit would greatly enhance the learning experience since the participants can perform the practical experiments along with the trainer.

Participants will be provided with reference material to continue their learning journey in the field of TinyML

The workshop is designed to provide a live and immersive experience where the participants will need to actively participate and perform the experiments along the the trainer. In order to maximize the learning potential, attendance is mandatory for the live sessions and recordings will not be provided.

While the objectives of the workshop can be achieved without a google account, it is highly recommended especially for beginners to avoid the hassles of installation of multiple softwares and libraries.

scikit-learn is used for various machine learning tasks, including classification (e.g., spam detection), regression (e.g., house price prediction), clustering (e.g., customer segmentation), and dimensionality reduction (e.g., PCA for feature selection). These are some of the areas you'll explore in the workshop.

Yes, we will use publicly available datasets, such as the Iris dataset or Breast Cancer dataset, which are provided directly within the scikit-learn library. You do not need to bring any datasets; they will be provided as part of the workshop materials.

No, prior experience with TensorFlow or deep learning is not required. However, some basic understanding of Python and machine learning concepts will help you grasp the topics more easily. The workshop will cover the basics of TensorFlow, so beginners are welcome.

Yes, TensorFlow can be run on most machines, but for optimal performance, especially with deep learning models, it's recommended to use a machine with a dedicated GPU. If you don't have access to a powerful machine, you can use cloud-based platforms like Google Colab, which provides free access to GPUs.

In this workshop, you will learn to build basic neural networks for classification and regression tasks, including models like Fully Connected Networks and Convolutional Neural Networks (CNNs). We will also cover how to train, evaluate, and improve these models.

Yes, the workshop will include hands-on coding sessions where you will implement neural networks using TensorFlow. You will learn how to define a model, train it on data, and evaluate its performance in real-time with practical exercises.